DataHour: Building and Operationalizing an Explainable Predictive Model

DataHour: Building and Operationalizing an Explainable Predictive Model

12 Jan 202315:01pm - 12 Jan 202316:01pm

DataHour: Building and Operationalizing an Explainable Predictive Model

About the Event

One of the main barriers in making decisions based on machine learning models is the lack of transparency. Basically, users and decision makers need to know how these models derive their conclusion and understand the underlying reasons. Addressing these questions is the essence of “explainability,” and getting it right is becoming essential.

During this session we will use a real-world use case to build a predictive model and then add the explainable AI at top of it to make the model transparent and interpretable for business users. 

In this DataHour, Amir will explain how to use Python packages OmniAXI as a model agnostic explainable AI. He will also cover how Streamlit and Flask deploy and operationalize both predictive and explanation models.

  1. Best articles get published on Analytics Vidhya’s Blog Space
  2. Best articles get published on Analytics Vidhya’s Blog Space
  3. Best articles get published on Analytics Vidhya’s Blog Space
  4. Best articles get published on Analytics Vidhya’s Blog Space
  5. Best articles get published on Analytics Vidhya’s Blog Space

Who is this DataHour for?

  1. Best articles get published on Analytics Vidhya’s Blog Space
  2. Best articles get published on Analytics Vidhya’s Blog Space
  3. Best articles get published on Analytics Vidhya’s Blog Space

About the Speaker

Amir Meimand

Amir Meimand

Principal Solution Engineer

Amir Meimand is a Principal Solution Engineer focusing on Data Science and Machine Learning. Amir has 10+ years experience in building, deploying, and applying advanced analytics to solve enterprise business problems. Previously, he was the director of Data Science at Zilliant, a SaaS company providing machine learning solutions for B2B industries, later acquired by Madison Dearborn.Amir’s current area of focus is scaling advanced analytics solutions by democratizing data science and machine learning. Amir holds a Ph.D. in Statistics and Operations Research from Pennsylvania State University, 2013.You can connect with him on Linkedin.

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